Director, product management | applied ai

We are looking for a product leader to run a portfolio that includes AI-powered products and to own how our Product Management team applies AI — the strategy, standards, investment decisions, governance and team capability. You will lead and develop a team of Product Managers, own product strategy and P&L across the portfolio, and raise the organization's product-AI capability. What "Applied AI" means at Director level. The emphasis shifts from doing the hands-on AI work to judging it, funding the right AI bets and setting the guardrails. This is a product-leadership role — not an engineering, data-science or AI-research role. You set direction and standards for the specialists who build.

Responsibilities

• Lead and develop a team of Product Managers running a portfolio that includes AI-powered products; own product strategy, vision and P&L across that portfolio
• Set an AI-informed product strategy — where AI creates durable advantage, where it is commoditizing, and how to sequence the roadmap against advancing AI capability
• Make build / buy / partner and investment decisions for AI capabilities; own AI business cases and ROI; fund the right experiments and know when to stop them
• Own AI-feature economics and lifecycle across the portfolio — cost, latency, unit economics, pricing, and model-lifecycle decisions (drift, versioning, vendor change)
• Set the standards, operating model and review gates for how the team builds AI features and uses AI in its own work, so quality and responsibility are consistent
• Own responsible-AI governance — privacy, bias, security, transparency, human oversight, audit trails, incident response, and applicable regulation (e.g., EU AI Act) and sector rules
• Raise the team's AI capability through coaching, playbooks, shared prompt/agent libraries and an AI component in the hiring bar; advise business units or clients on adoption
• Direct effective collaboration across product, engineering, data, design and AI/ML teams, keeping product intent, constraints and accountability clear
• Represent the organization credibly on its AI product strategy with senior clients — setting realistic expectations rather than over-promising

Requirements

• 7+ years in Product Management, having managed products, product lines/families and/or groups, with experience leading PM/PO teams; developed and/or launched 3+ products to market, including AI-powered products or capabilities
• Ownership of product vision, roadmap and P&L, and of strategic roadmap alignment across a portfolio
• Portfolio analysis and strategy formulation; prioritizing spend by ROI and supporting financial models — including AI business cases and build/buy/partner decisions
• Track record aligning product strategy with new technologies, assessing and adopting emerging AI capabilities responsibly
• SME across multiple (3+) business domains; deep grasp of consumer trends, technological disruption and competitive factors — including how AI is reshaping the domain
• AI literacy sufficient to lead — understands AI concepts, capabilities and limitations well enough to make sound portfolio and investment decisions and to challenge technical proposals credibly. ML-engineering / data-science depth is not required
• Able to shape company product strategy, convey difficult messages to senior stakeholders and own key initiatives and business KPIs
• Leads, develops and champions a team of Product Managers across a multi-product portfolio; identifies and plans for performance improvement
• Sets the operating model for how the team applies AI, and raises its proficiency through enablement, coaching and a clear hiring bar
• AI-informed product/portfolio strategy — advantage vs commoditization, build/buy/ partner, AI business cases and ROI, roadmap sequencing against AI capability
• Responsible-AI governance across the portfolio — privacy, bias, security, transparency, human oversight, audit trails/incident response and relevant regulation
• Ownership of AI-feature economics and lifecycle — cost, latency, unit economics, pricing, drift/versioning/vendor decisions
• Setting AI standards and review gates for how the team builds AI features and uses AI
• Raising team AI capability — enablement, coaching, playbooks, shared tooling, hiring bar
• Ability to evaluate AI outputs, prototypes and technical proposals and fund the right bets
• Working AI literacy — concepts, capabilities and limitations sufficient to lead and challenge
• Continued practical use of AI in own work and adaptability as AI evolves
• Ability to direct effective collaboration across engineering, data, design and AI/ML teams

Not required: building, training, fine-tuning or deploying ML models; data-science, MLOps or AI-research depth. The Director sets direction and standards for the specialists who do this work.

Nice to have

• Deep hands-on AI prototyping or feature-building (valued, but expected to plateau here — it is the Senior PM / IC strength; the Director's job is to judge and fund, not build)
• External thought leadership on AI product management (talks, publications, community)
• Direct experience standing up an AI governance or enablement program at organization scale